fraywing

Are these models harder to reason about given they produce tokens non-linearly? Especially since we rely on non-latent reasoning to know what the model is "thinking".

So like... do I get access?

This is mostly to be expected.

After Deno did layoffs we saw a consistent decline in announcements and innovation.

Sad day, but unsurprising.

> GPT‑6.1 Sol matches GPT‑6 Astra at roughly one-fifth of the cost

Astra is a pretty impressive model. Excited to try this.

It feels like the only thing left people are building are harnesses? Harnesses of harnesses?

Yeah, it's becoming challenging. A lot of that is because talent acquisition teams are either too heavily reliant on poor automation or they are the bottleneck in communication because of the application volume. Trying to fix that by making responses more deterministic and a first-class citizen. So if you are using a claw or Claude to apply, you get the ability to poll over the status yourself in a native way.

Ah, yeah. This is definitely more focused on creating structure to help reduce the "ATS black hole" problem as well as solve for candidate quality signals. It's anticipating headless ecosystem for hiring humans.

It's less about "AI said this guy" and more about proof, identity, and hopefully making getting seen as a candidate easier. Right now the signal/noise problem is progressively making that more difficult.

Hey there, totally understand your sentiment.

We have seven other companies involved that are listed on the website and have provided feedback for general use-cases -- given adoption curves are super hard, early traction we have around OJCP is encouraging to me. A lot more to do, but any help or ideas are greatly appreciated.

I'm chatting with other OSS organizations to help make sure this lands in no specific organizational control.